Title

An approach to direction finding based on a subspace perturbation expansion

Document Type

Conference Proceeding

Date of Original Version

12-1-2003

Abstract

This paper describes a method for estimating directions of arrival from sensor-array data. The estimates are obtained from minimizing a subspace-fitting cost function. This cost function is optimally weighted using statistical information provided by a subspace perturbation expansion. The calculations for scenarios involving very closely spaced sources suffers from the need to invert ill conditioned matrices. This problem is overcome by a reparameterization of both the cost function and its Jacobian based on the concept of a limiting subspace. The paper includes a challenging simulation example involving multiple moving sources.

Publication Title

Conference Record of the Asilomar Conference on Signals, Systems and Computers

Volume

1

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